Wind Rose
Chart overview
A wind rose is a circular histogram that simultaneously encodes wind direction frequency, wind speed class, and occurrence percentage for a given location and time period.
Key points
- Meteorologists, air quality scientists, and wind energy engineers rely on wind roses to characterize site climate, assess pollutant transport pathways, and evaluate turbine siting.
- They are a standard figure in environmental impact assessments and micrometeorological papers.
Python Tutorial
How to create a wind rose in Python
Use the full tutorial for implementation details, troubleshooting, and chart variations in matplotlib, seaborn, and plotly.
Complete Guide to Scientific Data VisualizationExample Visualization
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"Create a wind rose from my wind direction and speed data. Divide directions into 16 compass sectors, stack speed classes with distinct colors from a sequential colormap, label cardinal directions, show frequency percentage on the radial axis, and add a speed-class legend."
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Python Code Example
Console Output
Figure saved: plotivy-wind-rose.png
Common Use Cases
- 1Characterizing prevailing wind patterns at a proposed wind farm site
- 2Assessing dominant dispersion directions for industrial emission modeling
- 3Comparing seasonal wind climatology at an airport meteorological station
- 4Evaluating urban heat island ventilation corridors for city planning
Pro Tips
Use 16 sectors (22.5 degrees each) for detailed directional resolution rather than the default 8
Normalize bar heights to percentage of total observations so sites with different record lengths are comparable
Choose a sequential colormap with enough distinct steps to separate at least 5 speed classes
Set the radial axis label at 45 degrees to avoid overlap with the directional bars
Long-tail keyword opportunities
High-intent chart variations
Library comparison for this chart
matplotlib
Best when you need full control over axis formatting, annotation placement, and journal-specific styling for wind-rose.
numpy
Useful in specialized workflows that complement core Python plotting libraries for wind-rose analysis tasks.
Scientific Chart Selection Cheat Sheet
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